Credit

Documentation and Metadata

In order for your data to be used properly by you, your colleagues, and other researchers in the future, they must be documented. Data documentation (also known as metadata) enables you understand your data in detail and will enable other researchers to find, use and properly cite your data.

It is critical to begin to document your data at the very beginning of your research project, even before data collection begins; doing so will make data documentation easier and reduce the likelihood that you will forget aspects of your data later in the research project.

Researchers can choose among various metadata standards, often tailored to a particular file format or discipline. One such standard is DDI (the Data Documentation Initiative), designed to document numeric data files.

An excellent overview of what metadata is, examples of metadata, and common metadata standards (Dublin Core, Darwin Core, etc.)

(Link to Digital Curation at the University of Wisconsin-Madison, Research Data Services)

General Guidelines for Documentation

Following are some general guidelines for aspects of your project and data that you should document, regardless of your discipline. At minimum, store this documentation in a readme.txt file or the equivalent, together with the data. One can also reference a published article which may contain some of this information.

Title

Name of the dataset or research project that produced it

Creator

Names and addresses of the organization or people who created the data

Identifier

Number used to identify the data, even if it is just an internal project reference number

Subject

Keywords or phrases describing the subject or content of the data

Funders

Organizations or agencies who funded the research

Rights

Any known intellectual property rights held for the data

Access information

Where and how your data can be accessed by other researchers

Language

Language(s) of the intellectual content of the resource, when applicable

Dates

Key dates associated with the data, including: project start and end date; release date; time period covered by the data; and other dates associated with the data lifespan, e.g., maintenance cycle, update schedule

Location

Where the data relates to a physical location, record information about its spatial coverage

Methodology

How the data was generated, including equipment or software used, experimental protocol, other things one might include in a lab notebook

Data processing

Along the way, record any information on how the data has been altered or processed

Sources

Citations to material for data derived from other sources, including details of where the source data is held and how it was accessed

List of file names

List of all data files associated with the project, with their names and file extensions (e.g. 'NWPalaceTR.WRL', 'stone.mov')

File Formats

Format(s) of the data, e.g. FITS, SPSS, HTML, JPEG, and any software required to read the data

File structure

Organization of the data file(s) and the layout of the variables, when applicable

Variable list

List of variables in the data files, when applicable

Code lists

Explanation of codes or abbreviations used in either the file names or the variables in the data files (e.g. '999 indicates a missing value in the data')